PD5847 Sample Summary

## `summarise()` has grouped output by 'patient', 'age_at_sample_exact', 'age_at_sample', 'DOB', 'DATE_OF_DIAGNOSIS'. You can override using the `.groups` argument.
## Joining, by = "PDID"
patient ID age_at_sample_exact cell_type phase BaitLabel
PD5847 COLONY45 44.89802 BFU-E-Colony Colony NA
PD5847 PD5847i 44.91170 BM Gran Recapture PD5847i
PD5847 PD5847j 45.64271 PB Gran Recapture PD5847j
PD5847 PD5847k 45.91102 PB Gran Recapture PD5847k
PD5847 PD5847l 49.11157 PB Gran Recapture PD5847l

Tree

tree=plot_basic_tree(PD$pdx,label = PD$patient,style="classic")

Expanded Tree with Node Labels

The nodes in this plot can be cross-referenced with nodes specified in subsequent results. The plot also serves to give an idea of what the topology at the top of the tree looks like.

tree=plot_basic_tree(expand_short_branches(PD$pdx,prop = 0.1),label = PD$patient,style="classic")
node_labels(tree)

Timing of driver mutations (using Model = poisson_tree )

Note that the different colours on the tree indicate the separately fitted mutation rate clades.

Driver Specific Mutation Rates & Telomere Lengths by Colony & Timepoint

## 
## Random-Effects Model (k = 1; tau^2 estimator: REML)
## 
##   logLik  deviance       AIC       BIC      AICc 
##  -0.0000    0.0000    4.0000      -Inf   16.0000   
## 
## tau^2 (estimated amount of total heterogeneity): 0
## tau (square root of estimated tau^2 value):      0
## I^2 (total heterogeneity / total variability):   0.00%
## H^2 (total variability / sampling variability):  1.00
## 
## Test for Heterogeneity:
## Q(df = 0) = 0.0000, p-val = 1.0000
## 
## Model Results:
## 
## estimate      se     zval    pval    ci.lb    ci.ub 
##  17.9355  0.4921  36.4484  <.0001  16.9711  18.9000  *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## `summarise()` has grouped output by 'patient'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'patient'. You can override using the `.groups` argument.
node driver status child_count type colony_count mean_lambda_rescaled correction sd_rescaled lb_rescaled ub_rescaled median_rescaled p_lt_wt
-1 WT 1 -1 local 15 17.93552 1.01721 0.2421426 17.46584 18.42420 17.93146 NA
100 JAK2,9pUPD 1 77 local 6 21.14323 1.01721 1.2996510 19.18960 24.25722 20.92220 3.5e-04
187 DNMT3A 1 4 local 4 20.10593 1.01721 0.5447833 19.07923 21.20959 20.09224 5.0e-05
104 TET2:JAK2,9pUPD 1 71 local 71 23.06632 1.01721 1.6688739 20.27521 26.82576 22.90158 2.5e-05

Driver Acquisition Timeline

All ages are in terms of post conception years. The vertical red lines denote when colonies were sampled and blue lines when targeted follow up samples were taken.

patient node driver child_count lower_median upper_median lower_lb95 lower_ub95 upper_lb95 upper_ub95 N group age_at_diagnosis_pcy max_age_at_sample min_age_at_sample
PD5847 187 DNMT3A 4 0.0325864 0.1635204 0.0177970 0.0664861 0.1035941 0.3409181 5 DNMT3A 45.62355 49.83984 45.62628
PD5847 100 JAK2,9pUPD 77 0.0075348 26.3679458 0.0046611 0.0252664 24.6548616 28.9069826 5 JAK2 45.62355 49.83984 45.62628
PD5847 104 TET2 71 27.1489740 33.6900388 25.4655497 29.5969825 32.1823043 35.4263396 5 TET2 45.62355 49.83984 45.62628

Copy Number Variation and Timing

Summary of LOH timing inference

## Timings using the Clade Specific Rates
label node het.sensitivity chr start end nhet nhom mean_loh_event lower_loh_event upper_loh_event t_before_end t_before_end_lower t_before_end_upper kb count_in_bin count_se pmut pmut_se xmean xse_mean xsd x2.5. x50. x97.5. xn_eff xRhat lmean lse_mean patient driver3 child_count
9pUPD 100 0.9917 9 10469 47206190 0 10 24.75 20.4 26.44 1.743 0.04495 6.092 47200000 7744 88 0.01691 0.0001922 0.9342 0.0003936 0.06168 0.7699 0.9518 0.9983 24557 1 7.402 0.0006372 PD5847 JAK2,9pUPD 77

Duplications?

VAF Distribution of Targeted Follow Up Samples

Here we exclude all local CNAs and depict as color VAF plots